Tendon-driven continuum manipulators are widely used in minimally invasive surgeries. For example, bronchoscopies are a preferred approach to early diagnosis of lung cancer. In a conventional bronchoscopy procedure, a physician manually steers a long, flexible endoscope through the patient's airways. These steerable endoscopes are a class of tendon-driven continuum manipulators with a proximal handle that articulates the distal tip. Physicians rely on sensor feedback from an on-board camera and, in many procedures, an electromagnetic position sensor at the distal tip of the device. The position sensor is registered to a preoperative computed tomography (CT) of the patient's chest to provide a road map to the target site. Despite low complication rates (2.2%), there is significant variability in the diagnostic yield among institutions.
Robotic control of endoscopes in bronchoscopy procedures can potentially alleviate this variability and potentially improve patient outcomes, but autonomous control has proven difficult given the uncertainty in modeling the robot's interaction with the anatomy. Endoscopes and similar tendon-driven continuum manipulators control the end effector position through pull wires that bend the distal section of the device, referred to as the articulating region. Proximal to the articulating region, a decoupled, passive region complies to obstacles, allowing for atraumatic navigation through sensitive areas. The device's compliance results in unknown conformations as the anatomy applies unsensed constraints during a procedure. This presents significant challenges for traditional task-space control techniques that depend on an accurate model of the manipulator to solve for joint displacements and torques because the unsensed conformations change the response of the device in unintuitive ways.
Techniques that adapt to the environment are necessary for providing more intuitive or autonomous control of these devices in clinical settings. One approach is to introduce additional sensors along the body of the manipulator. Fiber Bragg gratings, for example, provide a potential solution to sensing the curvature of the entire manipulator; however, this technology is not yet clinically available. Another approach analyzes real-time ultrasound images in addition to a distal position sensor to determine the orientation of the device. Yet another approach is based on introducing a second position sensor at the junction of the articulating and passive regions, called the base of the manipulator, the model of the articulating region can be rotated, enabling inverse kinematics for closed-loop control.
Alternatively, the state of the robot may be estimated from the existing sensor at the distal tip of manipulators with a fixed base orientation and no passive section. One such approach, for example, estimates the orientation of the links in the HARP continuum manipulator, which has a “follow the leader” design so that each segment's position and orientation can be calculated relative to the fixed base. This type of estimation does not handle contact with the environment, and does not apply to manipulators with decoupled passive and articulating sections, which is characteristic of the majority of clinical catheters and endoscopes.
Despite these attempts, closed loop control remains a challenge for continuum manipulators having a passive region decoupled from an articulating region, and where the sensor is at the tip and not co-located with the base.